Our approach

How an engagement works

Every engagement moves from a funder's intent to a cost-estimated recommendation, with a different question and framework at each stage.

Frame

The question

What impact does the funder want to create, and for whom?

What we do

We work with the funder to turn their goals into a clear research question, agreeing who they want to reach, where, at what scale, and what level of impact they're aiming for.

How we approach it

We look at how important, neglected and solvable each problem is, a lens drawn from effective giving, to find where each additional rupee can do the most good.

Research

The question

Where is the need greatest, where can philanthropy make the most difference, and what works?

What we do

We map the need at a local level, look at what the government already spends, and bring together the evidence on which interventions work.

How we approach it

RIO’s “NLIO” lens: need, leverage, interventions and the organisations delivering them

An evidence hierarchy adapted from Cochrane, J-PAL and 3ie

Public data from NFHS, NITI Aayog, RBI, and central and state budgets

Estimate

The question

Which intervention does the most good per rupee?

What we do

We build cost-effectiveness models for the shortlisted interventions, adjusted for local conditions and tested against a range of assumptions.

How we approach it

Cost-effectiveness analysis adapted from GiveWell and Founders Pledge

Screen

The question

Which organizations can deliver this well, and put the funding to good use?

What we do

We identify organizations via our own search or an open call, screen for eligibility and evidence, and follow up with field visits and expert input.

How we approach it

We look at fit with the cause area, the capacity to absorb new funding, and basic compliance. We also assess the strength of each organization's own evidence and how faithfully it delivers its programmes.

Measure our impact

The question

Did our advice change where the money went?

What we do

Once the funder commits, we ask what they would have funded without our advice.

How we approach it

Funders split their commitment across three scenarios: it would have reached equally effective organizations anyway, gone to the cause without an evidence lens, or gone unspent. We then adjust for how confident they are in their answers.

Stage 01 of 05

Throughout, we test desk findings against people working in the states we study, because district statistics conceal much of what happens on the ground.

Need alone is an incomplete guide

Severe problems can still be weak places to give. Where proven interventions are scarce, or few organizations can deliver them well, additional funding is unlikely to go far.

Good work often goes unevaluated

Many strong Indian organizations have invested in programs ahead of formal evaluation. So we draw on the evidence behind the intervention and assess how well each organization delivers it.

How we choose cause areas

We chose where to research by asking where an additional rupee could move outcomes furthest.

While every cause area we consider matters, our choice reflects where we believe our research can add the most right now. We assessed six cause areas against four questions:

  1. 01 Sector maturity Is the sector mature enough to put more funding to good use?
  2. 02 Existing funding How much funding does it already receive?
  3. 03 Age of topic Is the problem likely to persist?
  4. 04 Government alignment Does it align with government priorities, so that philanthropy can help unlock public spending?
Six cause areas, four criteria
  • Sector maturity
  • Existing funding
  • Age of topic
  • Government alignment

Mental Health

Cleared the shortlist

Air Quality

Cleared the shortlist

Water and Food Systems

Cleared the shortlist

One Health

Cleared the shortlist

Early Childhood Care and Education

Cleared the full assessment

Income Enhancement

for smallholder farmers

Cleared the full assessment

The two selected areas combine an enduring problem, existing funding to build on, real policy salience, and a sector mature enough that additional money has somewhere productive to go. They also sit at opposite ends of the evidence spectrum: early childhood has a deep global evidence base that transfers imperfectly, while smallholder incomes required evidence to be assembled largely from the ground up.

How we treat evidence

We hold a fixed evidence bar, and widen what counts as evidence rather than lowering the standard.

For many interventions in India the upper rungs are empty, because the rigorous trials were run elsewhere. We triangulate strong international evidence with Indian public data, from sources such as NITI Aayog and the Reserve Bank of India, and with implementers' own monitoring data. The discipline lies in taking the best evidence seriously wherever it was produced, while being honest that an effect measured in one setting seldom transfers cleanly to another.

The evidence ladder
Evidence taxonomy
  1. Meta-analyses and systematic reviews
  2. Randomised controlled trials
  3. Quasi-experimental studies
  4. Cohort studies
  5. Pre-post studies
  6. Expert consensus
Cost-effectiveness, explained

Cost-effectiveness asks how much good each rupee does, and how that compares with the alternatives.

What it is

We express cost-effectiveness as a ratio of benefit to cost (BCR), which is a calculation of the benefit generated from an intervention at a given cost. A multiple of 10x means our model estimates that a programme creates ten times the value of the cost of the intervention given as a direct transfer. In livelihood work, value is the additional income a household earns over time; in early childhood, it is the gain in a child's development and earnings potential.

Why it matters

Programmes that appear similar can differ greatly in what they achieve per rupee. In early childhood, 60% of funding flows to interventions with an estimated 4–5x return, while options returning 15–80x remain underfunded. For a funder, where the money goes matters as much as how much is given.

How we calculate it

Every estimate rests on four inputs. We set out each one, with its source, for any funder who wants to check it.

Input What it captures Where it comes from
Cost What it capturesThe full cost of reaching a beneficiary, including delivery & overheads Where it comes fromImplementer budgets, verified in the field
Effect What it capturesHow much outcome changes for each beneficiary Where it comes fromThe strongest available studies, graded on our evidence ladder
Internal validity What it capturesHow much to trust that the study's effect is real in its own setting Where it comes fromStudy design, sample size, bias and attrition; effect shrunk toward zero where evidence is weak
External validity What it capturesHow far that effect carries to the local setting Where it comes fromDiscounts for context, baseline, delivery at scale, uptake, persistence and attribution, tested with practitioners

BCR=(Effect × Internal validity × External validity) ÷ Cost=value per dollar

How to read our numbers

Ranges, not single figures

Small changes in assumptions move the result, so every estimate carries a range.

Orders of magnitude, not fine distinctions

20x and 18x are effectively the same answer; 20x and 2x are not.

Within a cause area, not across them

Comparing a child's development with a farmer's income requires a judgement of values, which we leave to the funder.

Estimates, not measurements

They guide a decision before the money moves; they do not replace evaluation afterwards.

A worked example

Kangaroo Mother Care

In our research on early childhood, we identified ~30 interventions and Kangaroo Mother Care (KMC) was one of them. Kangaroo Mother Care, skin to skin contact for underweight newborns, is one of the most evidence-backed, low-cost interventions in newborn survival, recommended by WHO and linked to significant reductions in mortality and infection.

Trials claim Kangaroo Mother Care reduces newborn mortality by 40%. When evaluating KMC for Maharashtra, Raising Impact adjusted for local baseline practices, real-world scaling drop-offs, and bundled care attribution—refining the estimate down to a realistic ~14%. We bridge the gap between evidence and operational reality so funders can deploy capital with confidence.

The widely cited 40% reduction in newborn mortality became a working estimate of ~14% for Maharashtra.

Step & discount Resulting estimate Assumption Why
Starting point –
40%
AssumptionCochrane pooled mortality reduction, RR 0.60, from a subset of the 21 trials reviewed
WhyPooled from global trials across very different health systems; a ceiling, not an estimate
Discount 1: Informal care overlap × 0.85
34%
Assumption15% of eligible newborns already receive informal skin-to-skin contact
WhyInformal skin-to-skin contact already happens in Indian wards, narrowing the gain
Discount 2: scale up coverage × 0.60
20%
Assumption60% of eligible newborns receive the intervention once a programme operates at scale
WhyNot every eligible newborn receives the intervention once a programme scales beyond a trial
Discount 3: attribution × 0.70
14%
Assumption70% of the measured mortality benefit is attributable to KMC itself
WhyThe rest comes from the care bundle KMC usually travels with, including breastfeeding support
Working estimate –
~14%
Assumption40% × 0.85 × 0.60 × 0.70
WhyA little over a third of the headline figure

A global effect size is a starting point and the work lies in adjusting it for local conditions, one stated assumption at a time.

What’s the most good your giving can do in India?

If you’re a funder planning to make a significant philanthropic commitment, we would be glad to talk it through with you.

Write to info@raisingimpact.org